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Food plays a vital role in human sustenance and well-being, and the fluctuations in its price exert a significant impact on the attainment of the Sustainable Development Goals (SDGs) from social, economic, and environmental perspectives. This paper conducts an analysis utilizing data from 163 countries, revealing that an upsurge in global food commodity prices entails trade-offs with 13 SDGs, while exhibiting synergies with a few others. By considering specific food products, various types of countries, and the supply and demand shocks, further analysis confirms predominantly negative associations between spikes in food prices and the SDGs. Our findings highlight the urgent imperative to mitigate abrupt increases in food prices, such as those witnessed during the 2022 food crisis, to ensure the comprehensive fulfillment of the 2030 agenda for SDGs.
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Cities are at the heart of climate change mitigation as they account for over 70% of global carbon emissions. However, cities vary in their energy systems and socioeconomic capacities to transition to renewable energy. To address this heterogeneity, this study proposes an Energy Transition Index (ETI) specifically designed for cities, and applies it to track the progress of energy transition in Chinese cities. The city-level ETI framework is based on the national ETI developed by the World Economic Forum (WEF) and comprises two sub-indexes: the Energy System Performance sub-index, which evaluates the current status of cities' energy systems in terms of energy transition, and the Transition Readiness sub-index, which assesses their socioeconomic capacity for future energy transition. The initial version of the dataset includes ETI and its sub-indexes for 282 Chinese cities from 2003 to 2019, with annual updates planned. The spatiotemporal data provided by the dataset facilitates research into the energy transition roadmap for different cities, which can help China achieve its energy transition goals.
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As China's rapid urbanization continues, uneven urban population spatial distribution (UPSD) has a profound impact on its CO2 emissions. To understand how UPSD shapes CO2 emissions in China, this study employs geographic detectors to analyze the spatial stratified heterogeneity patterns of urban CO2 emissions and explore the spatial individual and interactive effects of UPSD in 2005 and 2015. Results show that CO2 emissions increased significantly from 2005 to 2015, especially in developed cities and resource-based cities. The spatial individual effect of UPSD on spatial stratified heterogeneity pattern of CO2 emissions has gradually increased in the North Coast, South Coast, the Middle Yellow River, and the Middle Yangtze River. The interaction of UPSD and urban transportation infrastructure, urban economic development, and urban industrial structure plays a more important role on the North Coast and East Coast than in other city groups in 2005. In 2015, the interaction between UPSD and urban research and development was the traction of mitigating CO2 emissions in developed city groups, especially on the North Coast and East Coast. Moreover, the spatial interaction between the UPSD and urban industrial structure has gradually weakened in developed city groups, which means UPSD drives the prosperity of the service industry, thus contributing to the low-carbon development of Chinese cities.
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Dióxido de Carbono , Urbanización , Humanos , Dióxido de Carbono/análisis , Población Urbana , Ciudades , China , Desarrollo Económico , Carbono , DemografíaRESUMEN
Cities' transition from fossil-based systems of energy production and consumption to renewable energy sources-the energy transition-is critical to mitigating climate change impact as cities' energy consumption and CO2 emissions account for two-thirds and over 70% of the world's total, respectively. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we used an Energy Transition Index (ETI) to characterize the city-level energy transitions from energy system performance and transition readiness dimensions. The ETI scores for 282 cities in China revealed a significant heterogeneity across cities and over time, and the gap between the cities in the top and bottom quartiles was persistent. We estimated that China's energy and carbon intensity could decrease by 34% and 32%, respectively, and that carbon per capita could fall by 17% if each city modestly follows the sustainable development path forged by the best performing cities with similar economic structures.
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Although China has developed the world's largest carbon emissions trading scheme (ETS), there is no official documentation explaining how the current sectoral coverage plan was determined and what sectoral rollout plan is preferred. Here, we contribute to the policy development of the world's largest carbon market by suggesting a priority list of industries be covered in the ETS. We estimated marginal abatement cost curves using a database of more than two million firms covering over 500 four-digit industries that account for more than 97% of total industrial emissions, and simulating various carbon market scenarios including thermal power, 13 designated, and an additional 50 industries that have high emissions or are covered in other ETSs. Our analysis suggests that the cement industry should be the next sector to be included in China's ETS. In our revised list, the average abatement cost can be reduced by 39.5-78.3% compared with the business-as-usual scenario.
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The Corona Virus Disease 2019 (COVID-19) has led to a decline in carbon emissions or an improvement in air quality. Yet little is known about how the pandemic has affected the "low-carbon" energy transition. Here, using difference-in-differences (DID) models with historical controls, this study analyzed the overall impact of COVID-19 on China's low-carbon power generation and examined the COVID-19 effect on the direction of the energy transition with a monthly province-specific, source-specific dataset. It was found that the COVID-19 pandemic increased the low-carbon power generation by 4.59% (0.0648 billion kWh), mainly driven by solar and wind power generation, especially solar power generation. Heterogeneous effects indicate that the pandemic has accelerated the transition of the power generation mix and the primary energy mix from carbon-intensive energy to modern renewables (such as solar and wind power). Finally, this study put forward several policy implications, including the need to promote the long-term development of renewables, green recovery, and so on.
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The outbreak of the COVID-19 epidemic has triggered adiscussion of the relationship between urbanization and the spread of infectious diseases. Namely, whether urbanization will exacerbate the spread of infectious diseases. Based on 31 provincial data from 2002 to 2018 in China, the impact of urbanization on the spread of infectious diseases from the dimensions of "population" and "land" is analyzed in this paper by using the GMM (generalized method of moments) model. The empirical study shows that the population increase brought by urbanization does not aggravate the spread of infectious diseases. On the contrary, urban education, employment and entrepreneurship, housing, medical and health care, and other basic public services brought by population urbanization can help reduce the risk of the spread of infectious diseases. The increasing density of buildings caused by land urbanization increases the risk of the spread of infectious diseases. Moreover, the impact of urbanization on the spread of infectious diseases has regional heterogeneity. Therefore, the prevention and control of disease play a crucial role.
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COVID-19 , Enfermedades Transmisibles , Enfermedades Transmisibles/epidemiología , Humanos , Pandemias , SARS-CoV-2 , UrbanizaciónRESUMEN
Economic shocks from COVID-19, coupled with ongoing US-China tensions, have raised debates around supply chain (or global value chain) organisation, with China at the centre of the storm. However, quantitative studies that consider the global and economy-wide impacts of rerouting supply chains are limited. This study examines the economic and emissions impacts of reorganising supply chains, using Australia-China trade as an example. It augments the Hypothetical Extraction Method by replacing traditional Input-Output analysis with a Computable General Equilibrium analysis. The estimation results demonstrate that in both exports and imports, a trade embargo between Australia and China - despite being compensated for by alternative supply chains-will cause gross domestic production losses and emissions increases for both countries and the world overall. Moreover, even though all other economies gain from the markets left by China, many of them incur overall gross domestic production losses and emission increases. The finding that the Association of Southeast Asian Nations and India may also suffer from an Australia-China trade embargo, despite a gain in trade volume, suggests that no country should add fuel to the fire. The results suggest that countries need to defend a rules-based trading regime and jointly address supply chain challenges.
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COVID-19 , Australia , China , Comercio , Humanos , SARS-CoV-2RESUMEN
In recent years, Shandong Province became one of China's largest carbon emitters; however, existing studies failed to capture the recent trends and the key driving factors behind it at the city level. In this study, we computed the city-level CO2 emission by employing accounting methods and Logarithmic Mean Divisia Index (LMDI) to provide a holistic picture and measure the contributing factors CO2 emissions across 16 cities in Shandong Province during 2010-2018. Research outcomes indicate that Shandong's CO2 emissions showed an increasing trend during 2010-2018, except in 2013. Shandong Province's GDP per capita and population size promote energy-related CO2 emissions from 2010 to 2018. Energy intensity is the main driving force behind Shandong's significant CO2 emission growth, followed by the energy consumption structure. Emission intensity and regional structure partly offset the CO2 emission increase. Industrial structure is the most important driving factor in reducing emissions; however, its emission reduction effect is not stable in some cities and sectors, especially for the nonmetal and metal industry, petroleum and chemical industry, and energy sector. Dongying is the top emitter across Shandong from 2010 to 2018. Its emissions mainly come from the petroleum and chemical industry. The largest driving factors are the energy intensity and industrial structure. Investigating CO2 emissions at the city level yields a strong recommendation that Shandong Province's regions cooperate to improve development patterns.
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The rapid development of China's manufacturing industry since China's accession to WTO in 2001 has dramatically increased China's carbon emissions. To inform the carbon policy development of China's manufacturing industry, this study constructed a DEA-GS (data envelopment analysis and grid search) model from a cost perspective to understand the their emission reduction characteristics. Using a large sample of manufacturing firms from 2008 to 2011, the carbon pricing and reduction potential of China's manufacturing firms was explored by analyzing the firms' marginal abatement costs. The results showed that: (a) with increasing marginal abatement costs, the growth rates of both cumulative emission reduction activities and emission reduction of these firms gradually slowed down. When the marginal abatement cost exceeds 200 Yuan/ton, neither the number of reduction activities nor the amount of reduced emissions increase. (b) The impact of marginal abatement costs on the numbers of reduction activities and firms in each sub-sector is heterogeneous. (c) The emission reduction behaviors of manufacturting firms, determined by carbon pricing, are mostly concentrated in developed areas or around large cities. In contrast, areas with substantial emission reductions are more scattered. The results suggest that The emission reduction characteristics of sub-sectors should be fully considered when formulating carbon policies for China's manufacturing industry. The carbon price for the China's manufacturing industry should not exceed 200 Yuan/ton. Furthermore, the carbon policy of China's manufacturing industry should have broader coverage, rather than merely covering developed areas.
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Carbono , Industrias , Carbono/análisis , Dióxido de Carbono/análisis , China , Comercio , PolíticasRESUMEN
As the largest contributor to production-based emissions, electricity generation sector has led to huge carbon emission transmissions. This is the first attempt to explore the latest features of carbon emission transmissions from electricity sector to the final domestic consumption of China in 2002-2015, combining MRIO-based Structural Path Analysis and transmission-based emission method. Results show that: (1) Although inter-provincial transmissions are increasing significantly, emission transmissions within intra-provincial trading are dominated. (2) 30 provinces are classified into two types, i.e., consumption centers and production centers. Both the inter-provincial transmission paths in consumption centers and production centers show the grid-level agglomeration and provincial heterogeneity. The inflow paths in consumption centers are mainly sourced from the production of Eastern China and South China, while the outflow paths for production centers are caused by the consumption in Central China, Guangdong and Jiangsu. Inter-provincial linkages are intensified and perform the feature of territorial propinquity. (3) Both intra-grid and inter-grid transmission nodes show an agglomeration trend of "electricity sector < intermediate sectors < electricity sector < consumption". These intermediate sectors include manufacture sectors, energy-intensive sectors and service sector. This paper provides policy implications on promoting low-carbon electricity cooperation across provinces and managing intermediate transmissions along supply chain.
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Electricity generation is the largest sector with decarbonization potential for China and the world. Based on the new emission factors, this paper aims to identify the structural and technological determinants of provincial carbon intensity in the electricity generation sector (CIE) using the multiplicative LMDI-II method. Results demonstrate that (1) China's overall CIE decreases by 7.3% in 2001-2015, and the research period can be divided into four stages according to CIE changes (i.e., rapid growth, rapid decline, slow growth, and transition). The CIE in the 12th FYP estimated in this paper, 24.9% lower than that using the emission factors from IPCC, is closer to China's actual situation. (2) There exists huge heterogeneity in the determinants of provincial CIE changes in four stages. CIE growth in the Northwest and Northeast is caused by the coal-dominated energy structure. CIE growth in the Southwest is attributed to the electricity structure effect, while that of the Coast region is caused by the geographic distribution effect. The electricity efficiency effect is attributed to the CIE growth for these regions and the Southwest should also place focus on the electricity trade effect. The impact of electricity trade-related factors depends on the region being a net exporter or importer of electricity. (3) To achieve carbon intensity reduction targets, 30 provinces are categorized into four types based on various combinations of structural and technological determinants. The findings provide insights into capturing future emission-mitigating focus as well as defining the emission-mitigating responsibilities between electricity exporters and importers in China.
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Carbono , Electricidad , Carbono/análisis , Dióxido de Carbono/análisis , China , Carbón Mineral , TecnologíaRESUMEN
Global change caused by carbon emissions alone has become a common challenge for all countries. However, current debates about urbanization and carbon emissions generally do not take into account the heterogeneities in urbanization and economic development levels. The goal of this study is to revisit the urbanization-emissions nexus by considering such heterogeneities in the Chinese context. The results reveal that there is significant heterogeneity in the total factor carbon emission performance index across provinces. Specifically, the relationship between carbon emission performance and urbanization reflects a U-shaped curve. Urbanization is found to have a stronger inhibiting effect on carbon emission performance when economic development levels improve. The results suggest that tailoring policies to each region's conditions, promoting investments in energy-saving and emissions-reducing technologies, and improving the use of public transportation could be mitigation strategies for global change that lead to low-carbon urbanization.
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As the largest sector with decarbonization potential, electricity generation is critical for achieving carbon intensity reduction targets of China by 2020 and 2030. This study combines temporal decomposition and scenario analysis to identify the key drivers and provinces with increasing carbon intensity of electricity generation (CIE) and designs four scenarios by integrating efficiency improvement and structural adjustment in 30 provinces of China, and estimates the possible reduction of CIE by 2020 and 2030. Results show that 1) CIE in China decreases by 7.25% during 2001-2015. The estimated CIE during 12th FYP in this study is 25% lower than the estimation using IPCC emission factors, which is closer to China's reality. 2) Driving forces of CIE changes in 30 provinces vary greatly across provinces. The increasing CIE in four worse-performance regions (i.e. Northeast, South Coast, Southwest, Northwest) is mainly caused by energy mix effect and geographic distribution effect. The CIE growth in South Coast is also related to thermal power share effect. 3) Both 2020/2030 targets can be achieved by regulating the drivers for CIE growth in 30 provinces (i.e., RAK scenario). CIE decline is concentrated in three types of provinces, namely provinces with large economic size, strong policy support and clean energy implementation. The findings and recommendations provide insights into achieving 2020/2030 targets for CIE reduction.
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PROBLEM: Empirical studies on the effectiveness of workplace safety regulations are inconclusive. This study hypothesizes that the asynchronous effects of safety regulations occur because regulations need time to become effective. Safety regulations will work initially by reducing the most serious accidents, and later by improving overall safety performance. METHOD: The hypothesis is tested by studying a provincial level aggregate panel dataset for China's coal industry using two different models with different sets of dependent variables: a fixed-effects model on mortality rate, which is defined as fatalities per 1,000 employees; and a negative binominal model on the annual number (frequency) of disastrous accidents. RESULTS: Safety regulations can reduce the frequency of disastrous accidents, but have not reduced mortality rate, which represents overall safety performance. DISCUSSION AND SUMMARY: Policy recommendations are made, including shifting production from small to large mines through industrial consolidation, improving the safety performance of large mines, addressing consequences of decentralization, and facilitating the implementation of regulations through carrying on institutional actions and supporting legislation. IMPACT ON INDUSTRY: Until recently, about 4,000 coal miners perished annually in China, demonstrating that workplace safety in China's coal industry is an urgent and important issue. This research provides evidence that safety regulations have asynchronous effects and identifies the priorities in improving safety in China's current coal mining. This may assist the Chinese government to design more effective safety improvement policies and improve the effectiveness of safety regulations and safety performance.